Exploring Student Acceptance of Artificial Intelligence in Engineering Design

• In Event: Artificial Intelligence (AI) for Cognition and Learning

Abstract

Learners’ self-efficacy in domain knowledge and AI technology are essential in fostering acceptance of AI in solving authentic tasks. This study extended the technology acceptance model by refining the self-efficacy theory. The proposed model was tested among 114 high school students from two suburban high schools in the Midwestern United States, who utilized AI feedback to enhance their engineering design solutions. Results from the partial least squares structural equation modeling revealed that domain knowledge self-efficacy positively influenced students’ perceived ease of use. Moreover, students’ perceived ease of use was indirectly influenced by their AI technology self-efficacy. Findings from this study provide valuable insights into the use and implementation of AI in STEM education.

Authors

• Juan Zheng, Lehigh University

• Jiayan Zhu, Lehigh University

• Shan Li, Lehigh University

• Rundong Jiang

• Charles Xie, Institute for Future Intelligence